code: def drnl_node_labeling(self, edge_index, src, dst, num_nodes=None):
      # Double-radius node labeling (DRNL).
      src, dst = (dst, src) if src > dst else (src, dst)
      adj = to_scipy_sparse_matrix(
          edge_index, num_nodes=num_nodes
      ).tocsr()
  
      idx = list(range(src)) + list(range(src + 1, adj.shape[0]))
      adj_wo_src = adj[idx, :][:, idx]
  
      idx = list(range(dst)) + list(range(dst + 1, adj.shape[0]))
      adj_wo_dst = adj[idx, :][:, idx]
  
      dist2src = shortest_path(
          adj_wo_dst, directed=False, unweighted=True, indices=src
      )
      dist2src = np.insert(dist2src, dst, 0, axis=0)
      dist2src = torch.from_numpy(dist2src)
  
      dist2dst = shortest_path(
          adj_wo_src, directed=False, unweighted=True, indices=dst - 1
      )
      dist2dst = np.insert(dist2dst, src, 0, axis=0)
      dist2dst = torch.from_numpy(dist2dst)
  
      dist = dist2src + dist2dst
      dist_over_2, dist_mod_2 = dist // 2, dist % 2
  
      z = 1 + torch.min(dist2src, dist2dst)
      z += dist_over_2 * (dist_over_2 + dist_mod_2 - 1)
      z[src] = 1.0
      z[dst] = 1.0
      z[torch.isnan(z)] = 0.0
  
      self._max_z = max(int(z.max()), self._max_z)
  
      return z.to(torch.long)
  
imports: import math
  import os.path
  import time
  from itertools import chain
  import numpy
  import torch
  import torch.nn.functional
  from scipy.sparse.csgraph import shortest_path
  from sklearn.metrics import roc_auc_score
  from torch.nn import BCEWithLogitsLoss, Conv1d, MaxPool1d, ModuleList
  from torch_geometric.data import Data, InMemoryDataset
  from torch_geometric.datasets import Planetoid
  from torch_geometric.loader import DataLoader
  from torch_geometric.nn import MLP, GCNConv, SortAggregation
  from torch_geometric.transforms import RandomLinkSplit
  from torch_geometric.utils import k_hop_subgraph, to_scipy_sparse_matrix
label_desc: Use image node_id 5 for calling the SEALDataset obj's underlying member method code with example usage: obj.drnl_node_labeling(edge_index, src, dst, num_nodes) and returns: z